It is desirable to estimate the position (or “location”) of persons and things in a geographic area with a reasonable degree of accuracy. Accurate estimations of a position can be used to speed up emergency response times, track business assets, and link a consumer to a nearby business. Various techniques are used to estimate the position of an object (e.g., a receiver), including trilateration, which is the process of using geometry to estimate a location of an object using distances traveled by different signals that are received at a location of the object, where the signals are transmitted from geographically-distributed beacons. Reliable distance measurements between the object and beacons are often not possible when the object is in an indoor environment, since signals from outdoor beacons are never received or are received only after traveling extended distances while reflecting off of many surfaces. The lack of reliable distance measurements typically results in imprecise estimates of the object's position within the venue, which sometimes erroneously place the object outside the venue.
Other issues arise when an object approaches the edge of a beacon network, which may frequently occur in a localized network of beacons that covers a small, localized area (e.g., the inside of a building). When the object is close to a boundary/edge of the localized area, an “edge effect” taints the accuracy of position estimates. Thus, detecting when the object is at or near the edge of the localized area becomes critical, as does estimating the object's position without relying only on the beacon network.
Accordingly, there is a need for improved techniques of locating objects using a localized beacon network in localized areas (e.g., indoor environments).